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The purpose of this paper is to examine the impacts of fiscal policy, namely, net tax and government expenditure on national saving and its nonlinearity. The author first investigates whether the impacts of fiscal policy on national saving have changed after the global financial crisis of 2008. Then, the author tests the nonlinearity of the relationship by taking account of the economic cycle, namely, economic expansion (boom) and economic recession (bust).

The empirical model bases on a reduced-form equation with national saving as a dependent variable, lagged value of national saving, output gap and fiscal policy as independent variables. The two-step system GMM approach was employed to estimate the empirical model, using a panel of 23 emerging Asian economies in the period of 1990-2015.

The empirical results show that tax policy and expenditure policy follow the predictions of the overlapping generation model with finite horizon and the Keynesian view. The nonlinearity of fiscal policy is twofold. The conduct of fiscal policy in the period after 2008 seems effective, while the effect is insignificant in the period before 2008. Likewise, fiscal policy tends to have more significant effects in bust cycle. The effect of tax policy is increased during recession, while the effect of government spending is more pronounced during economic downturn.

The contributions of this paper are twofold. First, it is shown that fiscal policies in the region had more impacts on national saving after the global financial crisis of 2008. Second, the research confirms nonlinear impact of fiscal policy on saving behavior during economic recession and economic boom.

This paper aims to investigate the mutual dependence between housing prices and housing credit in Estonia, a country that experienced rapid debt accumulation during the 2000s and big swings in house prices during that period.

The authors use Bayesian econometric methods on data spanning 2000–2015.

The estimations show the interdependence between house prices and housing credit. More importantly, negative housing credit innovations had a stronger effect on house prices than positive ones.

The asymmetry in the linkage between housing credit and house prices highlights important policy implications, in that if central banks increase capital buffers during good times, they can release credit conditions during hard times to alleviate the negative spillover into house prices and the real economy.

This research's main objective is to investigate the relationship between consumption expenditure and consumer confidence in the USA and to study their effects on US economic revivalism during and after the coronavirus disease 2019 (COVID-19) shock.

The authors use Michigan's monthly Consumer Sentiment Index and its five components from January 1978 to April 2020. The study is unique in quantifying the potential variations in US consumer confidence due to COVID-19 under different scenarios, by providing a projection until December 2021. It also estimates the time needed for recovery and offers guidance to policymakers on ways to contain the negative impacts of COVID-19 on the economy by restoring consumer confidence.

All scenarios show a gradual recovery of consumer confidence and consumption expenditure. This study recommends expansionary policies to encourage consumption expenditure to generate additional demand and boost economic growth and job creation.

Though this study is limited to the US consumer confidence index, it offers significant implications for marketers, customers and policymakers of other developed economies. The authors recommend expansionary economic policies to boost consumer confidence, raise economic growth and result in job creation.

The study is unique in quantifying the potential variations in US consumer confidence due to COVID-19 under different scenarios; by providing a projection until December 2021. It also estimates the time needed for recovery and guidance for policymakers on ways to contain the COVID-19 shock negative impacts on the economy by restoring consumer confidence.

The purpose of this paper is to analyze the changes in wealth and consumption inequality in Spain and estimate the consumption effects of housing and financial wealth.

The estimations are made using micro-data from the Spanish Survey of Household Finances (2002–2014) applying cross-section, panel and interquartile techniques.

The findings of this paper suggest that there was an increase in wealth inequality during the period under analysis and a reduction in consumption inequality. Also, the authors find a significant positive effect of wealth on consumer expenditure. Disaggregating by asset type, the value of the main residence is the category with the highest estimated effect on consumption, whereas the remaining types of assets, although still positive and generally significant, have more modest effects on consumption. However, the estimated coefficients and their significance can change substantially depending on the phase of the economic cycle and the position of the household in the income distribution.

These results provide new empirical evidence on the effects of household wealth changes on their consumption behavior, the differences depending on the household's position in the distribution and the fluctuations of these estimated coefficients throughout a period of profound economic upheavals.

A controversy about whether liberalization through market opening is a necessary and sufficient condition for a stable and balanced growth in the developing countries was retriggered by the 2008 global financial crisis. This paper aims to analyze 1) the impact of market openness on the economic growth and financial development, 2) the dynamic correlation between the compositional change in foreign investments and the returns of domestic financial markets, 3) the effect of foreign portfolio investment on the stock market activity (liquidity and profitability). Our empirical findings infer that the income level has a positive relationship with financial openness and the foreign portfolio investments cause price fluctuations in the domestic stock market. These results imply that the precautionary and effective policies such as prudential regulations on the short-term capital transactions are strongly needed to emerging markets in order to prevent the excessive fluctuations in the financial markets over the macroeconomic fundamentals.

This study analyses agricultural land price dynamics in order to better understand price development and to improve forecast accuracy. Understanding the evolution of agricultural land prices is important when considering sound investment decisions.

This study applies threshold autoregression to model agricultural land prices. The data includes quarterly observations on Finnish agricultural land prices.

The study shows that Finnish agricultural land prices exhibit regime-switching behaviour when using past changes in prices as a threshold variable. The threshold autoregressive model not only fits the data better but also improves the accuracy of price forecasts compared to the linear autoregressive model.

The results show that a sharp fall in agricultural land prices temporarily changes the regular development of prices. This information significantly improves the accuracy of price predictions.

The purpose of this paper is to provide a dating system for the Italian residential real estate market from 1927 to 2019 and investigate its interaction with credit and business cycles.

To detect the local turning point of the Italian residential real estate market, the authors apply the honeycomb cycle developed by Janssen et al. (1994) based on the joint analysis of house prices and the number of transactions. To this end, the authors use a unique historical reconstruction of house price levels by Baffigi and Piselli (2019) in addition to data on transactions.

This study confirms the validity of the honeycomb model for the last four decades of the Italian housing market. In addition, the results show that the severe downsizing of the housing market is largely associated with business and credit contraction, certainly contributing to exacerbating the severity of the recession. Finally, preliminary evidence suggests that whenever a price bubble occurs, it is coincident with the start of phase 2 of the honeycomb cycle.

To the best of the authors’ knowledge, this is the first time that the honeycomb approach has been tested over such a long historical period and compared to the cyclic features of financial and real aggregates. In addition, even if the honeycomb cycle is not a model for detecting booms and busts in the housing market, the preliminary evidence might suggest a role for volume/transactions in detecting housing market bubbles.

The purpose of this paper is to compare different models’ performance in modelling and forecasting the Finnish house price returns and volatility.

The competing models are the autoregressive moving average (ARMA) model and autoregressive fractional integrated moving average (ARFIMA) model for house price returns. For house price volatility, the exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model is competing with the fractional integrated GARCH (FIGARCH) and component GARCH (CGARCH) models.

Results reveal that, for modelling Finnish house price returns, the data set under study drives the performance of ARMA or ARFIMA model. The EGARCH model stands as the leading model for Finnish house price volatility modelling. The long memory models (ARFIMA, CGARCH and FIGARCH) provide superior out-of-sample forecasts for house price returns and volatility; they outperform their short memory counterparts in most regions. Additionally, the models’ in-sample fit performances vary from region to region, while in some areas, the models manifest a geographical pattern in their out-of-sample forecasting performances.

The research results have vital implications, namely, portfolio allocation, investment risk assessment and decision-making.

To the best of the author’s knowledge, for Finland, there has yet to be empirical forecasting of either house price returns or/and volatility. Therefore, this study aims to bridge that gap by comparing different models’ performance in modelling, as well as forecasting the house price returns and volatility of the studied market.

The purpose of this study is to focus deeply on the short term to explain the relative long-term evolution of the Argentinian economy in the long and the short term.

The study of the long-term evolution of the Argentine economy and identifying the moment in which it began to lose ground compared to other developed economies, such as Australia and Canada, constitutes the central axis of the historiography of this country. However, an additional problem presented by the Argentine economy is its high volatility. For this reason, the long term should be influenced by the short term, an issue that requires a more detailed study of the cyclical behavior and a deep analysis of the relationship between the long and the short term.

The results obtained point to a cyclical development that influences the long-term evolution and, therefore, explains Argentina’s convergence process with Australia and Canada. Frequent deep busts and short booms characterize the Argentine cycle, offsetting its long-term growth potential.

Although the long term has been profusely studied in Argentina, the short term has not been analyzed to the same extent, which is surprising given the extreme volatility of this economy (Prebisch, 1950). The studies performed on economic cycles have always been partial, disconnected from the long term and carried out without much technical rigor.

The study aims to estimate the short- and long-run effects of monetary policy on residential property prices in South Africa. Over the past decades, there has been a monetary policy shift, from targeting money supply and exchange rate to inflation. The shifts have affected residential property market dynamics.

The Johansen cointegration approach was used to estimate the effects of changes in monetary policy proxies on residential property prices using quarterly data from 1980 to 2022.

Mortgage finance and economic growth have a significant positive long-run effect on residential property prices. The consumer price index, the inflation targeting framework, interest rates and exchange rates have a significant negative long-run effect on residential property prices. The Granger causality test has depicted that exchange rate significantly influences residential property prices in the short run, and interest rates, inflation targeting framework, gross domestic product, money supply consumer price index and exchange rate can quickly return to equilibrium when they are in disequilibrium.

There are limited arguments whether the inflation targeting monetary policy framework in South Africa has prevented residential property market boom and bust scenarios. The study has found that the implementation of inflation targeting framework has successfully reduced booms in residential property prices in South Africa.